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Title

midas hmc -- Bayesian estimation via Hamiltonian Monte Carlo (CmdStan)

Syntax

midas hmc
tp fp fn tn
[if exp]
[in range]
,
id(varlist)
covariance(structure)
modelfile(filename)
[standir(path)
outputfile(filename)
chains(#)
warmup(#)
iter(#)
thin(#)
seed(#)
adaptdelta(#)
maxtreedepth(#)
threads(#)
threadsperchain(#)
variational
vialgorithm(string)
convergestats
showcode
log
hpd
level(#)
noheader
nocoefficients
nosummary
nofitstat
hetstats
hsroc
revman]

Description

midas hmc fits the bivariate random-effects model using the
No-U-Turn Sampler (NUTS), a variant of Hamiltonian Monte Carlo, via
CmdStan. It provides superior mixing compared to midas mh for
complex posterior geometries.

CmdStan must be installed and the Stan model file must be provided.
See mc-stan.org/cmdstan for installation.

Key options

covariance(structure) covariance prior structure.
Same options as midas mh. Required.

modelfile(filename) path to the Stan .stan model file. Required.

standir(path) CmdStan installation directory.

warmup(#) warmup iterations per chain. Default 1000.

iter(#) sampling iterations per chain. Default 2000.

adaptdelta(#) target acceptance rate (0-1). Higher values
reduce divergences. Default 0.8.

maxtreedepth(#) maximum tree depth for NUTS. Default 10.

threads(#) total threads for within-chain parallelism.

variational uses variational inference instead of MCMC.

showcode displays the Stan model code.

log displays the CmdStan sampling log.

Example

. midas hmc tp fp fn tn, id(author) covariance(cholesky) modelfile(bivar.stan) warmup(1000) iter(2000)

Also see

midas, midas mh, midas inla, midas bayesplot